In our study, we tackle two practical challenges as follows: 1) we consider a realistic setting in which the number of queries that can be used to obtain training data for the generative model is strictly limited and 2) the problem of solving (REF ) is NP-hard with an exponential complexity in searching for the two sets \(G_T\)  and \(S\) .Since our problem maps to the original IM problem when \(G_T \equiv G\) , the proof of NP-hardness similarly follows that of the original problem [1]}. This motivates us to present an accurate and low-complexity solution to this problem in (REF ).
